Table of Contents

Welcome to the course website for “Multimedia Data Mining” SoSe 2018! This lecture gives an introduction to social multimedia processing and extracting information from images, videos, and other multimedia content. The focus will be on retrieval, search, and filtering of concepts, objects, and scenes.

  • Lecturers: Dr. Damian Borth, Prof. Andreas Dengel, and guest lecturer (Dr. Christian Schulze and Marco Schreyer)
  • Credits: 2C+1R, 4 credit points
  • Language: English
  • Level: Master (entry level)
  • Requirements
    • Introduction to Pattern Recognition (recommended, but not required)
    • Introduction to Image Processing and Image Understanding (recommended, but not required)
    • basic probability theory and analysis
  • Literature (available in computer science library):
    • Ian Goodfellow, Yoshua Bengio,Aaron Courville: Deep Learning, 2017
    • Duda, Hart, Stork: Pattern Classification, 2nd edition
    • Gonzalez, Woods: Digital Image Processing
    • Bishop: Pattern Recognition and Machine Learning
  • Exam: written


  • October 20: The review sessions for MDM 2018 Exam2 shall take place on October 26, Friday from 15:00-17:00 at Wittgenstein (DFKI, 3rd Floor).
  • October 14: The review sessions for MDM 2018 Exam2 have been postponed to next week (the week which starts at October 22) because of requests from some students and certain unplanned events. The exact date and location shall be announced shortly this week.
  • October 12: MDM 2018 Exam 2 Results are online: Please use the following link: results
  • September 28: MDM 2018 Exam2 on 01.10.2018 at 09:30 - 10:30, room 46-280
  • August 22:The review session for the exam sheets (Einsicht) will take place on Friday, 24th August at DFKI between 3:00pm - 5:00pm in Room Wittgenstein (3rd floor)
  • August 22: MDM 2018 Exam 1 Results are online: Please use the following link: results
  • July 10th: Slides of lecture 13 are online.
  • July 03rd: Slides of lecture 12 are online.
  • July 03rd: Slides of lecture 11 are online.
  • June 25th: Exercise session on June 27th will take place in DFKI Room Bayes (2.04) @ 2pm.
  • June 18th: Slides of lecture 10 are online.
  • June 18th: Tutorial for Sheet 3 will take place June 27th, 2pm, DFKI (room will be announced on the website)
  • June 12th: Slides of lecture 07 and 09 are online.
  • June 5th: Slides of lecture-08 are online.
  • May 22th: Slides of lecture-06 are online.
  • May 15th: Slides of lecture-05 are online.
  • May 15th: exercise sheet is online.
  • May 8th: Slides of lecture-04 are online.
  • May 6rd: exercise sheet is online.
  • May 3rd: Slides of lecture-03 are online.
  • April 24th: There will be no tutorial on Wednesday April 25th. Our first tutorial will be May 9th.
  • April 18th: Slides of lecture-02 are online.
  • April 16th: Slides of lecture-01 are online.
  • April 11th: First lecture takes place on Wednesday 8:15-9:45 in 48-208.
  • April: Lecture starts today!



  • Damian Borth
  • Contact email (all requests)
    • Managed by Tushar
  • Registration for the class to help us organizing the class
    • please register with an email to providing the following information:
      • Name
      • email
      • field of study
      • do want to take the exam?


Lecture schedule:

block date lecturer content details slides & demos exercise sheets & materials
1 11.04.18 Damian Borth Introduction course formalities, introduction slides -
2 17.04.18 Damian Borth Multimedia Information Systems definitions, setup, labels, benchmarking slides -
3 24.04.18 Damian Borth no lecture - - Ipython/Jupyter Installation link
4 01.05.18 → 02.05.18 Damian Borth 17:15 @ 46-260:: Pattern Recognition (supervised) basic decision theory, classification, classifier combination slides sheet NumPy Website NumPy Tutorial
5 08.05.17 Damian Borth Pattern Recognition (unsupervised) clustering, dimensionality reduction slides -
6 15.05.17 Damian Borth Text Retrieval document retrieval, retrieval models, relevance feedback, data structures slides sheet, URL list, material
7 22.05.17 Damian Borth Image Representation definitions, features and their properties, invariance, global features, local features slides -
8 29.05.17 Christian Schulze Similarity Search applications, prototypical architecture, distance measures, object search slides -
9 05.06.18 Damian Borth Visual Recognition and Image Classification 1 terminology, applications, face detection, face recognition, object recognition, visual words slides sheet material
10 19.06.18 Christian Schulze Video Analysis shot boundary detection, keyframe extraction, motion estimation & applications, audio analysis slides -
11 12.06.18 Damian Borth Visual Recognition and Image Classification 2 Bag-of-Words, Support Vector Machine (SVM), Spatial Location Extension, Concept Vocabularies slides -
12 26.06.18 Damian Borth Deep Learning 1 - DL 101 and Autoencoders end-to-end learning, neural networks, autoencoder slides Neural Network Playground
13 03.07.18 Damian Borth Deep Learning 2 Convolutional Neural Networks, Long-short Term Memory Networks, Generative Adversarial Networks slides -
14 10.07.18 Damian Borth Deep Learning 3 Visual Sentiment Analysis, AdjectiveNounPairs, DeepSentiBank slides -

Last modified:: 20.10.2018